AIMC Topic: Artificial Intelligence

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Detecting microcephaly and macrocephaly from ultrasound images using artificial intelligence.

BMC medical imaging
BACKGROUND: Microcephaly and macrocephaly, which are abnormal congenital markers, are associated with developmental and neurologic deficits. Hence, there is a medically imperative need to conduct ultrasound imaging early on. However, resource-limited...

Beyond Benchmarks: Evaluating Generalist Medical Artificial Intelligence With Psychometrics.

Journal of medical Internet research
Rigorous evaluation of generalist medical artificial intelligence (GMAI) is imperative to ensure their utility and safety before implementation in health care. Current evaluation strategies rely heavily on benchmarks, which can suffer from issues wit...

User Intent to Use DeepSeek for Health Care Purposes and Their Trust in the Large Language Model: Multinational Survey Study.

JMIR human factors
BACKGROUND: Generative artificial intelligence (AI)-particularly large language models (LLMs)-has generated unprecedented interest in applications ranging from everyday questions and answers to health-related inquiries. However, little is known about...

Novel Blended Learning on Artificial Intelligence for Medical Students: Qualitative Interview Study.

JMIR medical education
BACKGROUND: Artificial intelligence (AI) systems are becoming increasingly relevant in everyday clinical practice, with Food and Drug Administration-approved AI solutions now available in many specialties. This development has far-reaching implicatio...

Unveiling the potential of artificial intelligence in revolutionizing disease diagnosis and prediction: a comprehensive review of machine learning and deep learning approaches.

European journal of medical research
The rapid advancement of Machine Learning (ML) and Deep Learning (DL) technologies has revolutionized healthcare, particularly in the domains of disease prediction and diagnosis. This study provides a comprehensive review of ML and DL applications ac...

Fetal origins of adult disease: transforming prenatal care by integrating Barker's Hypothesis with AI-driven 4D ultrasound.

Journal of perinatal medicine
INTRODUCTION: The fetal origins of adult disease, widely known as Barker's Hypothesis, suggest that adverse fetal environments significantly impact the risk of developing chronic diseases, such as diabetes and cardiovascular conditions, in adulthood....

New care pathways for supporting transitional care from hospitals to home using AI and personalized digital assistance.

Scientific reports
Transitional care may play a vital role in the sustainability of Europe's future healthcare system, offering solutions for relocating patient care from hospital to home, therefore addressing the growing demand for medical care as the population is ag...

Differentiability of voice disorders through explainable AI.

Scientific reports
The voice can be affected by various types of pathology. The phoniatric medical examination is the acoustic analysis, which evaluates the characteristic parameters extracted from the vocal signal. Computer-assisted decision-making systems can help sp...

Investigating the factors influencing users' adoption of artificial intelligence health assistants based on an extended UTAUT model.

Scientific reports
As an emerging healthcare technology, artificial intelligence (AI) health assistants have garnered significant attention. However, the acceptance and intention of ordinary users to adopt AI health assistants require further exploration. This study ai...

Unlocking the potential of essential oils in aromatic plants: a guide to recovery, modern innovations, regulation and AI integration.

Planta
Essential oils recovered from aromatic plants hold tremendous potential across diverse fields, which include therapeutic, industrial, and technological domains. Integrating advanced recovery techniques, regulatory frameworks, and AI-driven innovation...